@inproceedings{zehle-etal-2026-promptolution,
title = "promptolution: A Unified, Modular Framework for Prompt Optimization",
author = "Zehle, Tom and
Hei{\ss}, Timo and
Schlager, Moritz and
A{\ss}enmacher, Matthias and
Feurer, Matthias",
editor = "Croce, Danilo and
Leidner, Jochen and
Moosavi, Nafise Sadat",
booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
month = mar,
year = "2026",
address = "Rabat, Marocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.eacl-demo.21/",
pages = "282--296",
ISBN = "979-8-89176-382-1",
abstract = "Prompt optimization has become crucial for enhancing the performance of large language models (LLMs) across a broad range of tasks. Although many research papers demonstrate its effectiveness, practical adoption is hindered because existing implementations are often tied to unmaintained, isolated research codebases or require invasive integration into application frameworks. To address this, we introduce promptolution, a unified, modular open-source framework that provides all components required for prompt optimization within a single extensible system for both practitioners and researchers. It integrates multiple contemporary discrete prompt optimizers, supports systematic and reproducible benchmarking, and returns framework-agnostic prompt strings, enabling seamless integration into existing LLM pipelines while remaining agnostic to the underlying model implementation."
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<abstract>Prompt optimization has become crucial for enhancing the performance of large language models (LLMs) across a broad range of tasks. Although many research papers demonstrate its effectiveness, practical adoption is hindered because existing implementations are often tied to unmaintained, isolated research codebases or require invasive integration into application frameworks. To address this, we introduce promptolution, a unified, modular open-source framework that provides all components required for prompt optimization within a single extensible system for both practitioners and researchers. It integrates multiple contemporary discrete prompt optimizers, supports systematic and reproducible benchmarking, and returns framework-agnostic prompt strings, enabling seamless integration into existing LLM pipelines while remaining agnostic to the underlying model implementation.</abstract>
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%0 Conference Proceedings
%T promptolution: A Unified, Modular Framework for Prompt Optimization
%A Zehle, Tom
%A Heiß, Timo
%A Schlager, Moritz
%A Aßenmacher, Matthias
%A Feurer, Matthias
%Y Croce, Danilo
%Y Leidner, Jochen
%Y Moosavi, Nafise Sadat
%S Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Marocco
%@ 979-8-89176-382-1
%F zehle-etal-2026-promptolution
%X Prompt optimization has become crucial for enhancing the performance of large language models (LLMs) across a broad range of tasks. Although many research papers demonstrate its effectiveness, practical adoption is hindered because existing implementations are often tied to unmaintained, isolated research codebases or require invasive integration into application frameworks. To address this, we introduce promptolution, a unified, modular open-source framework that provides all components required for prompt optimization within a single extensible system for both practitioners and researchers. It integrates multiple contemporary discrete prompt optimizers, supports systematic and reproducible benchmarking, and returns framework-agnostic prompt strings, enabling seamless integration into existing LLM pipelines while remaining agnostic to the underlying model implementation.
%U https://aclanthology.org/2026.eacl-demo.21/
%P 282-296
Markdown (Informal)
[promptolution: A Unified, Modular Framework for Prompt Optimization](https://aclanthology.org/2026.eacl-demo.21/) (Zehle et al., EACL 2026)
ACL
- Tom Zehle, Timo Heiß, Moritz Schlager, Matthias Aßenmacher, and Matthias Feurer. 2026. promptolution: A Unified, Modular Framework for Prompt Optimization. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 282–296, Rabat, Marocco. Association for Computational Linguistics.